> Synaptic connections mediate classical intercellular communication in the brain. However, recent data have demonstrated the existence of noncanonical routes of interneuronal communication mediating the transport of materials including calcium, mitochondria, and pathogenic proteins such as amyloid beta (Aβ). Using super-resolution and electron microscopy, Chang et al. identified and characterized structures called nanotubular bridges that connect dendrites in the brain (see the Perspective by Budinger and Heneka). These bridges mediate the transport of calcium ions, small molecules, and Aβ peptides, and may contribute to the spreading and accumulation of pathological Aβ in Alzheimer’s disease. —Mattia Maroso
Penrose’s vindication: In a broad philosophical sense. His intuition that quantum effects might play some role in cognition seems less far-fetched now than it did 30 years ago.
But vindication of Orch OR specifically (microtubule-based quantum gravity collapses driving consciousness) not yet.
If you’ve listened to anything he’s said in the last few years he doesn’t hold very tightly to the microtublule explanation.
Paraphrasing what he said in a video from a year ago or so: it’s an interesting theory that he’d like to see tested, but he has no idea whether it’s correct or not.
Would do a lot to explain many's understanding of the brain as a non-deterministic machine (or, their reasonable resistance to the idea that it is a deterministic one)
that seems kind of pointless to speculate about? unless you were into reading this sort of thing a long time ago and it is interesting to you? aren't there more convincing modern models of consciousness that don't rely on spookiness?
yes, it's microtubules, but there's no sign of any weirdness here. and Penrose's whole theory is "quantum is weird and I think brains are weird, so brains must be quantum. so where can we find some quantum stuff?"
No, nothing to do withPenrose’s idea. No quantum effects just the traditional use of microtubules for transport of cargo — in this case between adjacent dendrites.
Until we both discover everything down to the Planck length, and then prove somehow that the Planck length is truly the smallest "unit", then we have not discovered everything. And we have probably hardly discovered anything, relatively.
Of course, that's specifically about human anatomy. In this case we're talking about a feature that I'd bet is present in other animals too, so the factors discussed here don't all apply. In this case though there seems to be a straightforward answer -- the structures involved are very small! The post I linked is largely talking about larger structures we failed to find...
I still think there's a good chance that evolution has figured out some way to leverage quantum computation, probably in a very different way from the way we're trying to do it with ultra-cold low noise quantum digital circuits. If this is the case it's going to be some kind of high temperature noisy analog stochastic way of harnessing QC. The phrase "stochastic analog quantum computer" comes to mind.
It's how little energy the brain uses, especially for learning. The brain seems to be hundreds of thousands to millions of times more energy efficient than any kind of current AI on a classical computer, not to mention still beating it in terms of performance and versatility. Transistors do not use millions of times more energy than synapses, and processor feature sizes are not millions of times larger. Something else is going on.
Either the brain is leveraging QC or our AI training algorithms are just really really horrible compared to whatever is happening in biology. Maybe biology found learning methods that work thousands of times better than differential backpropagation.
I like the possibility of QC in brain. However, explaining why brain is much more efficient that computers does not need QC. Computers and Brain evolved in two completely different ways. For the brain, simple cognitive functions emerge first, supporting more complex life behaviours, starting with very simple multi celular life forms. Logical reasoning emerges much later, and is pretty expensive. Then we made computers to do logical computation and they are incredibly efficient at it: a modern low power processor is much more efficient than human brain in this kind of workload, by orders of magnitude.
Now we are trying to implement what the mind is naturally good at with systems designed to do logic well. This is the main reason it's so inefficient. Emulation is costly. It is costly when brain does logic, and is costly when computers do AI.
In theory, we should be able to build computing devices designed for AI workloads, and they can be as efficient as brain or even much better.
The brain 'stores' data without using power. Under classical synapse structure, it modifies the butons to modulate the charges and neurotransmitters passing and being received. This is memristance.
It's very low energy to do this and it keeps for decades (probably). It's not a quantum effect.
Be aware though, this is a 'classical' synapse understanding. The neurons are doing all kinds of other things too, they are alive after all. And the glia, the glia and astrocytes affect memory too, but we're still trying to understand how.
Look, don't jump to quantum stuff with the brain.
It's just really hard to get data, low sample sizes, and desperate need of grant funding.
And then you have AI “specialist “ like Hinton doing thought experiments saying if we replaced a neuron with ones we made we would still be conscious exactly the same way
The same thing is hypothesized for most tissue in the body and a source of how cancer seems to spread without direct connectivity. It's been classified so often as just background curioso that it never was investigated further.
Hopefully finer grained imaging will elludicdate this stuff.
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[ 2.9 ms ] story [ 55.6 ms ] thread> Synaptic connections mediate classical intercellular communication in the brain. However, recent data have demonstrated the existence of noncanonical routes of interneuronal communication mediating the transport of materials including calcium, mitochondria, and pathogenic proteins such as amyloid beta (Aβ). Using super-resolution and electron microscopy, Chang et al. identified and characterized structures called nanotubular bridges that connect dendrites in the brain (see the Perspective by Budinger and Heneka). These bridges mediate the transport of calcium ions, small molecules, and Aβ peptides, and may contribute to the spreading and accumulation of pathological Aβ in Alzheimer’s disease. —Mattia Maroso
"Discovery of quantum vibrations in 'microtubules' inside brain neurons supports controversial theory of consciousness"
https://www.sciencedaily.com/releases/2014/01/140116085105.h...
But vindication of Orch OR specifically (microtubule-based quantum gravity collapses driving consciousness) not yet.
https://royalsocietypublishing.org/doi/10.1098/rsta.1998.025...
Paraphrasing what he said in a video from a year ago or so: it’s an interesting theory that he’d like to see tested, but he has no idea whether it’s correct or not.
yes, it's microtubules, but there's no sign of any weirdness here. and Penrose's whole theory is "quantum is weird and I think brains are weird, so brains must be quantum. so where can we find some quantum stuff?"
Until we both discover everything down to the Planck length, and then prove somehow that the Planck length is truly the smallest "unit", then we have not discovered everything. And we have probably hardly discovered anything, relatively.
Of course, that's specifically about human anatomy. In this case we're talking about a feature that I'd bet is present in other animals too, so the factors discussed here don't all apply. In this case though there seems to be a straightforward answer -- the structures involved are very small! The post I linked is largely talking about larger structures we failed to find...
It's how little energy the brain uses, especially for learning. The brain seems to be hundreds of thousands to millions of times more energy efficient than any kind of current AI on a classical computer, not to mention still beating it in terms of performance and versatility. Transistors do not use millions of times more energy than synapses, and processor feature sizes are not millions of times larger. Something else is going on.
Either the brain is leveraging QC or our AI training algorithms are just really really horrible compared to whatever is happening in biology. Maybe biology found learning methods that work thousands of times better than differential backpropagation.
Now we are trying to implement what the mind is naturally good at with systems designed to do logic well. This is the main reason it's so inefficient. Emulation is costly. It is costly when brain does logic, and is costly when computers do AI.
In theory, we should be able to build computing devices designed for AI workloads, and they can be as efficient as brain or even much better.
The brain 'stores' data without using power. Under classical synapse structure, it modifies the butons to modulate the charges and neurotransmitters passing and being received. This is memristance.
https://en.wikipedia.org/wiki/Memristor
It's very low energy to do this and it keeps for decades (probably). It's not a quantum effect.
Be aware though, this is a 'classical' synapse understanding. The neurons are doing all kinds of other things too, they are alive after all. And the glia, the glia and astrocytes affect memory too, but we're still trying to understand how.
Look, don't jump to quantum stuff with the brain.
It's just really hard to get data, low sample sizes, and desperate need of grant funding.
It's not quantum.
Hopefully finer grained imaging will elludicdate this stuff.